There exist many theoretically successful algorithms for episodic reinforcement learning [1]}, [2]}, [3]}, [4]}, [5]}, [6]}. The majority of these are built under the assumption that the feedback is immediate or, at the very least, received at the end of each episode. This allows the agent to quickly learn about the quality of their decisions and adapt to take better actions.
